Clinicians, confronted with a multitude of complex and pivotal decisions throughout a patient’s healthcare journey, often rely on population-level averages, intuition, and incomplete patient records.

Meanwhile, the electronic health record (EHR) is a rich repository of unnormalized clinical data, documentation, and patient attributes both structured and unstructured. EHRs are primarily focused on record-keeping and billing, but with AI we are maximizing the value of this data by transforming EHRs into a system of intelligence designed to enhance the care of patients and deliver a comprehensive understanding of each patient.

To that aim, The future of healthcare AI hinges on the convergence of three critical elements: a comprehensive grasp of a patient’s unique history, transparency, and the application of causal inference. In this talk, Dr. Christine Swisher will describe Ronin’s innovative approach to melding these three elements, such that every clinical decision is rooted in data, personalized for a given patient, and rendered efficiently with confidence. In addition, how the quick ability to test and apply John Snow Labs SOTA clinical NLP models enable our data science team to iterate quickly and effectively, without the added overhead of data curation and implementation. Finally, Dr. Swisher will shed light on how Ronin empowers healthcare professionals to provide personalized care that enhances outcomes for cancer patients.